Department of Urology, University of Iowa, Iowa City, Iowa, USA.
Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Neurourol Urodyn. 2024 Apr;43(4):893-901. doi: 10.1002/nau.25363. Epub 2024 Jan 22.
This study tested the hypothesis that ecological momentary assessment (EMA) of pelvic pain (PP) and urinary urgency (UU) would reveal unique Urologic Chronic Pelvic Pain Syndrome (UCPPS) phenotypes that would be associated with disease specific quality of life (QOL) and illness impact metrics (IIM).
A previously validated smart phone app (M-app) was provided to willing Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) participants. M-app notifications were sent 4-times daily for 14 days inquiring about PP and UU severity. A clustering algorithm that accounted for variance placed participants into PP and UU variability? clusters. Associations between clusters and QOL and IIM were then determined.
A total of 204 participants enrolled in the M-app study (64% female). M-app compliance was high (median 63% of surveys). Cluster analysis revealed k = 3 (high, low, none) PP clusters and k = 2 (high, low) UU clusters. When adjusting for baseline pain severity, high PP variability, but not UU variability, was strongly associated with QOL and IIM; specifically worse mood, worse sleep and higher anxiety. UU and PP clusters were associated with each other (p < 0.0001), but a large percentage (33%) of patients with high PP variability had low UU variability.
PP variability is an independent predictor of worse QOL and more severe IIM in UCPPS participants after controlling for baseline pain severity and UU. These findings suggest alternative pain indices, such as pain variability and unpredictability, may be useful adjuncts to traditional measures of worst and average pain when assessing UCPPS treatment responses.
本研究旨在验证以下假设,即通过对盆腔疼痛(PP)和尿紧迫性(UU)进行生态瞬时评估(EMA),可以揭示出独特的慢性盆腔疼痛综合征(UCPPS)表型,这些表型与特定疾病的生活质量(QOL)和疾病影响指标(IIM)相关。
向愿意参加多学科慢性盆腔疼痛研究(MAPP)的参与者提供了一个经过验证的智能手机应用程序(M-app)。在 14 天内,M-app 每天发送 4 次通知,询问 PP 和 UU 的严重程度。一种聚类算法考虑了方差,将参与者分为 PP 和 UU 变异性聚类。然后确定聚类与 QOL 和 IIM 之间的关联。
共有 204 名参与者参加了 M-app 研究(64%为女性)。M-app 的依从性很高(中位数为 63%的调查)。聚类分析显示,PP 有 k=3(高、低、无)聚类,UU 有 k=2(高、低)聚类。在调整基线疼痛严重程度后,高 PP 变异性而非 UU 变异性与 QOL 和 IIM 密切相关,具体表现为情绪更差、睡眠更差和焦虑程度更高。UU 和 PP 聚类彼此相关(p<0.0001),但高 PP 变异性的患者中有很大一部分(33%)UU 变异性较低。
在控制基线疼痛严重程度和 UU 后,PP 变异性是 UCPPS 参与者 QOL 更差和 IIM 更严重的独立预测因子。这些发现表明,在评估 UCPPS 治疗反应时,疼痛变异性和不可预测性等替代疼痛指标可能是传统最差和平均疼痛测量的有用补充。